Monday, January 13, 2020

Coming Soon: The Data Lab

I know it's been quiet here...but I'm still around, thinking and working on various things. My latest data story will be complete this week. It's taken a few months to represent nearly 10,000 data points, but it is looking good. More on that soon.

But today, I want to commit publicly to what's next.

It's been a challenging year at work. I still enjoy my job a lot, but not necessarily the conditions I have to currently work under. Enough said. So, as I've been talking with others about this and pondering what I want to do, I have found myself thinking about what I want. What would my job look like? And in the midst of all that, I developed what I started calling "Crazy Idea #1" and "Crazy Idea #2."

Crazy Idea #1: Community-based Data Story
I've pushed out our district data stories into the community for the last couple of years, but what if I helped the community push out one of its own? What if I worked with an organization that needed community input on their strategic plan or other goals? What if we linked with other districts to leverage our data and resources?

And, crazy or not, this idea is in motion. I've identified an organization that is working to help students in our area build their capacity to connect with their neighbourhoods and community. I've talked with my counterparts in other districts about some data that we have in common to share. And soon, I'll be working with a few thousand students to create a data story that we will share at our city's spring arts walk. It's terrifying and inspiring...the perfect intersection of emotions to get me excited about going to work (regardless of whoever and whatever else is there).

But most importantly, I plan to use Crazy Idea #1 to launch something even crazier.

Crazy Idea #2: The Data Lab
You see, what I really want to do is support people in using data to answer their own questions and tell their own stories. And while not all of those stories need to take a physical shape, I can honestly say that getting your hands involved builds understanding. So, to that end, I want to develop a physical space for people to come and work with data.

I see this as a storefront in our downtown area. The front would have some retail options—journals, art supplies, all manner of sticky notes, and anything else you might need for capturing and representing ideas with data. But the biggest part of the store would be a conference space...something with flexible furniture, idea paint on the walls, carts with materials, a large screen, and anything else needed for learning. I see this as a place to host workshops on all sorts of topics, data walks, group work/planning, and more. It will be a lab for building stories. I want it to have a 3D printer and laser engraver and band saw.

And my audience? Being in the state capital, there are plenty of options—from lobbyists to state agencies to schools to community-based organizations. Most importantly, I want it to be a place where all are welcome and that underrepresented groups can have their voices lifted. I want to support and grow others.

But to get there, I have to build my reputation outside of school districts and demand among other organizations. I need some time to build capital (social and monetary) through consulting so I can have enough momentum to launch the physical space. Crazy Idea #1 is going to be one of those steps.

In the meantime, I have commissioned the logo you see above. (It's not finalized yet...we're still making a few edits.) I am teaching a class on data use at a local university this spring, and that will give me an opportunity to test out some hands-on workshop ideas. I've purchased a couple of domains. And I'm off to meet with the local center for women in business to try and get smart about that side of things.

When I talk about this idea with people who know me and know my work, they all see the potential. And while I know that they're biased (as am I), I've also never been so clear on what I want in my life...not even when I picked teaching for a career. I realize that there will be lots of twists and turns on the path ahead...plenty of setbacks and disappointments...and that the final product will be different from the vision I have now. But I accept that as part of the bargain.

What do you think? Any feedback on the logo or ideas? Are there people I should talk to who do similar work? What else would you advise?

Wednesday, August 7, 2019

Nine: Chart a Course

I'm so excited to share this project with you. It's been a long time since I felt like there was some magic in the air...and when The Muse came back, she did so with a vengeance.

This is a story about whether students who have similar paths (in the form of schools, teachers, and courses) experience similar outcomes (in the form of performance).

The Data
There are a lot of data packed into the representation of each student: gender, race, with/without disability, eligible/not eligible for free/reduced lunch, performance level for grades 3 - 7 on the state math assessment, teacher for grades 3 - 7. I built a template to pull these pieces from our student information system, but beyond that, I did not need to transform any of the data—no formulas, pivot tables, etc.

I did generate an alias for every student and teacher, because I fed their connections (which student had which teacher/course) into the Connect the Dots tool on I will explain the reason for this later on in this post.

The Build
The entire display is paper and glue, with map pins to attach each "student" to a board. That's it. The representations were built by quilling paper. I love that these data look fragile, but I have to tell you that the pieces are strong and resilient...much like our students. Also like our students, nearly all of them are unique.

Here's what you're looking at for a student. The star is made of 5 rays, representing the five grade levels (3 - 7). Grade 3 is in the 12 o'clock position, and the rest follow as you move clockwise around the star. If a student didn't attend one of our schools for a given grade level, there is no ray at that position.

The paper colour for each ray shows what the performance level was on the state math assessment for that grade. Orange is level one (well below standard), yellow is level two (below standard), light blue is level three (at standard), and dark blue is level four (above standard). Each ray is wrapped in a piece of coloured paper to indicate a particular teacher/school. We have six elementary schools serving grades 3 - 5, so there are six sets of colours: orange, purple, green, blue, red, and yellow. There are two middle schools serving grades 6 - 7, represented by blue and red. If a student attended one of our schools at a given grade level, but didn't take the test, the ray has the outer wrapper and is empty for the performance level.

On the inside of each star are four round disks of paper in white (w) and grey (g).

Note that we did not have any non-binary students at this grade level last year, so male and female were the only categories. I also collapsed our students of colour into one category, and while I strongly believe that this is not best practice, I am also legally obligated to protect personally identifiable information about students. At this grade level, we have some racial populations with only two or three students. When faced with a choice of leaving race out of the conversation completely or summarizing it into two categories...I chose Option B. Certainly, there are other data points I could have selected here, such as attendance or discipline. But I like that the center of the star includes some "internal" attributes that students bring with them, while the outer rays represent the "external" pieces in the form of teachers and system outcomes.

Here is a small group of students that shows the variations by missing grade levels, missing scores, gender, etc:

Now that I had 452(!) of these objects, I needed to figure out the connections between them. This is where the Connect the Dots tool helped. For each school, I uploaded a coded list of students and teachers. The online tool produced a network diagram like the one below, but more importantly, it provided me with a table showing me who was in each group, as well as the connections.

I selected the stars in each group and laid them out as a constellation. I placed stars that had teachers/courses in common closer together. Most of our elementary schools had 6 or 7 constellations. Here is one of them (before labels).

Each elementary school was organized on its own 24" x 36" cork board that had been covered in fabric. Stars were attached with map pins and then annotations were added to share what the group had in common. The six schools were organized into two sets of three, because we have two feeder patterns into middle school. This allows a look across the district.

Lessons Learned
When people use the phrase "labour of love," I will now know what they mean. I personally wove every piece of paper used in this display. I spent about 300 hours total building this story out of 3200 pieces of paper and a bottle of glue. Most of the work was done during my summer vacation: early mornings, late nights, weekends, at home and while visiting others. I drank a ton of coffee (mostly decaf, I promise). I got glue all over everything—my computer, my dining table, me. I have never devoted so much time and energy to creating one of these stories. But it was all worth it. This is the most beautiful display I've ever built. But beyond that, it is fascinating to look at. There is so much meaning packed into this. It captures and holds one's attention.

One of the things I have to remind myself is that when I uploaded the information about students and teachers, that was it—no information about gender, race, etc. And yet, it is obvious with some of groups that they have some of these attributes in common. In other words, the system either does or does not support certain types of kids. Now, this is not new learning, especially at a large scale level. But we are talking about small groups here. Let me give you one example. For students who take the advanced math track on one side of our district, one school only placed males there...the second nearly all males...but the third placed about even numbers by gender. What was most interesting about this third school is that nearly every girl who was in this track and successful in math had the same third grade teacher. That one teacher was the common denominator...and that group was different from every other in the district. And until I built this display, I would never have seen this. I was also surprised at how different every student appeared. Yes, I know that every child is an individual, but this display really drives it home. While there are a few (but not many!) students who had the same five teachers, they did not have the same internal attributes or the same outcomes.

If you'd like to see more pictures or learn more about our data stories project in our school district, please visit the companion page on our district web site.

Tuesday, August 6, 2019

Eight: Unmasking LAP

I have had this post in my queue for a few months. Last school year was a hard year, for a variety of reasons...and I didn't feel like publishing to create any reminders of it. But I have something super-special (finally!) to share tomorrow, so I'm pushing this one out the door today.

I finally built and shared my first data story for the 2018 - 2019 school year. While I originally had some big plans for data stories this year — including community involvement — this has not turned out to be anything like a normal school year. I'll spare you the gory details, but just say that the impact of all the turmoil has been that I mostly don't feel interested in creating anything...even though my passion for this project remains. So, over the last three months, I have been chipping away at doing something and hoping that this will rekindle some joy.

I have been wanting to look at our intervention data. In our state, supplemental funding is provided via the Learning Assistance Program (LAP). The goal is to work with students who are at least one grade level behind in reading or math and accelerate their learning so they can meet grade level expectations. Our district uses nearly all this funding in our elementary schools to buy teacher and paraeducator time. These interventionist use a "pull out" model where students come to a separate space each day for up to 30 minutes of extra instruction, tutoring, and support. Each school determines which grade levels to serve, which area (reading or math), how to group students, and what materials to use. There are a lot of variables, but the bottom line is really about outcomes.

What I've noticed over the last several years is that once a student is identified for LAP services, they rarely make enough progress to exit the program. The primary reason why they leave the program is that it's the end of the school year and there's no more time. However, the news isn't all bad, but it's still challenging to identify what it means for the program to be effective.

The Data
For this story, I pulled student performance data from fall and winter for every K - 5 student who has been served in LAP this year. I wanted to look at both growth and proficiency across schools. I also wanted to show some of the difference in the populations we serve — for example, a student with low-performance might receive support at one school, but not another, just because of program capacity and the volume of students to serve.

After I pulled assessment data for each of these students, I found the raw difference between the number of points earned between fall and winter. I compared that with the amount of growth necessary to maintain an "at grade level" performance between those two time points and identified each of the LAP students as having less than or at least that amount of growth.

The Build
I used Sculpey clay and a mold to create a face for each student. We have six elementary schools, so six colours (orange, blue, purple, red, green, brown) were used. The clay was tinted to create a gradation of each colour to represent the number of years the student had spent in the intervention program. More years equaled a darker hue. Faces representing students who had made more than the required amount of grade level growth were attached to a pin so they would stick out from the board, creating a 3D effect.

 I used six boards, one for each grade level. Students were placed on the board based on how much overall growth they had made between fall and winter. This was not an exact placement—I used a bit of artistic license to group students. My goal was to create a mask shape with the faces, with the idea that we were trying to reveal something about the program.

Lessons Learned
I have to admit that this was not my favourite project to do. It was important from the standpoint that I needed to get back into producing stories again and this forced me to at least think about communicating with data. However, it did reveal some things about our intervention program, including that it's not particularly effective. Considering the state gives us nearly 2 million dollars to run it, I'm not convinced it's a good investment of taxpayer dollars. This is not to say that students don't grow or that for some individuals it provides good support. It doesn't mean that there aren't some adults in our buildings busting their rears to make a difference for students. But if the goal is to get every child to be able to perform at grade level for reading...well, there's not a lot of good news in this story. When I think about the students who have spent multiple years in the program, I wonder why we keep exposing them to the same intervention and expecting a different outcome. What should we be doing instead? We still haven't had that conversation in our district and honestly, I don't know if anyone is interested in doing that.

Monday, February 25, 2019

You Can Count on Me

I don’t remember where I first read about these programmable buttons from Amazon. Sure, many of us have seen the “Dash” versions you can get which allow you to place an order at the click of a button, but there is potential for more. And while I’ll let your own minds wander to all of the possibilities, I just want to talk about one: using these as data collection devices.

You can configure each button to communicate over wifi. It can receive and transmit data related to a single, double, or long click. Slip one in your pocket. What are the kinds of things you might like to track? How many minutes in a class period the teacher is talking…or how many boys, girls, or non-binary students s/he calls on? What if you gave one to a student and asked him/her to push a button every time an adult in the building greeted him or her by name? We could even go bigger. What if you put a set in the office with a different question each week and asked visitors to respond?

I had these and other questions in mind. So, last summer, we ordered one of these Amazon Internet of Things (IoT) Buttons for our office…and since then, it’s been sitting in its little box, staring at me, waiting for its opportunity to be useful. When I found myself with a gift of time this week, I decided it was finally the moment to program the little beast. Now it’s time to share my learning with you, in case you want to jump in on this, too.

My only disclaimer here is that what I know about coding would fit in a thimble. There will be, no doubt, more elegant solutions to what I implemented—and if you know them, I hope that you’ll share. Here are the resources on which I relied most heavily:
  • Caroline Dunn has a great video on YouTube to help you set up your button and get you started. The code and IFTTT recipes have some useful background, but they did not work for me “as is.”
  • This code from Joseph Guerra, however, works like a dream. The only limitation is that it shows you how to capture information from a single click—not the double or long-click (if you want to use all three options with one button).
  • To overcome this last issue, I was able to use some code from here. I still had to figure out where to place it…but I did. And you can, too.
You will need
I won’t get into the nitty-gritty here with the button set up—watch Caroline’s video or hit teh Googles for some additional support. Basically, you’ll install the apps on your mobile device and use those to configure the button to a designated wifi source and select its first task. 

Next, set up your IFTTT (If This, Then That) recipes. You'll need three: one for a single click, one for a double click, and one for a long click. Use the Webhooks app as the trigger (If then...) and the "add a row" option from Google Sheets (...then that) to capture the type of click. Even though you set this stuff up first, it's really the second part of what happens when the button gets pushed. But you need some information from this to add to the first part of process.

So let's take care of that. Log into your Amazon AWS account and find the Lambda app. This is where your code for the button lives. There's some placeholder stuff there from when you first configured the button using the app on your smartphone. Delete that and replace it with the stuff from Joseph Guerra. You'll be all set for one type of click (single, double, or long). If you want to have the button collect two or all three types of clicks, modify the code so it looks like the sample below. Note that you're just copying the stuff for your first click type (e.g., Single) and pasting it in two more times for Double and Long. Replace the words "Single" with the other clicks.

That's it. You can do it. I did---and I didn't even have this to get started. Keep in mind that you can modify your code here to associate different names with your IFTTT recipes (applets). If you don't want single, double, long showing in your spreadsheet, you can have yes, no, maybe or thumbs up and thumbs down. Or start and stop. The possibilities might not be endless, but the variations are completely up to you.

What I like about the button is not just its options for simplified, automated, and "mobile" data collection, but also the anonymous nature of it. The Google Sheet only captures a timestamp and click type (or whatever word you tell it). When I handed the button off to a principal to use in his building, I told him that whatever shows up in the spreadsheet is all his---I don't need to know who he gave the button to or what the clicks represent or what questions he had in mind. As long as he can extract what meaning he needs, then that's all that matters. And even if the spreadsheet was public, the data won't mean anything to anyone who doesn't know what the various clicks represent.

Now that I survived my first foray into this world, I'm ready to go further. We ordered 19 more of the buttons and I will get started this week getting those programmed and ready to check out to principals. I'm excited to see all the different ways that they use these to gather information in their buildings.

What will you do with yours?

Saturday, July 7, 2018

Road Map

I consider myself an organized person, but not much of a planner. At least, I don't do a lot of long term planning. I have never had a career path that I've mapped out. I didn't decide I wanted to be a teacher until the month I graduated from college...and since then, I've more or less fallen into different jobs when recognized Opportunity knocking at the door. I am also a fan of her sister,  Serendipity. In fact, this is one of the reasons why my current home is my favourite place I've ever lived. There are little bits of magic and wonder to be found every day. I don't offer or condone any of this as the best approach to life. I am always in awe of those who have clear goals and seem to be driven toward them. It just hasn't been my experience...and I am okay with this.

So, imagine my surprise when, by chance, I found myself writing a theory of action, developing a logic model, and outlining a plan for some long-term goals with a data initiative. Who the hell am I becoming in my old age? But if you've been following my journey here over the last year or so, maybe some of what I share below will not be a surprise. In fact, I'm hoping that some of you might like to play along, too.

Theory of action
Here is my current, messy thinking: 
If we increase data literacy in ourselves and others, then participation in conversations at school and with the community will become more equitable, and then structural and institutional barriers to education will be reduced.
I've spent a lot of time in the last couple of years trying to ground myself in what I believe about data and the purpose it serves in education. I might summarize this as that I don't think that we can solve problems by representing our data in the same ways and having the same conversations as we have before. Whether your call it an achievement gap, opportunity gap, or educational debt, the bottom line is that we've been well aware of disproportionate outcomes for a long time...and yet another bar chart showing this isn't going to be the thing that creates change. I won't claim that I have THE answer or any sort of magic bullet, but I do have something different. I think that's the best place to start.

The plan
I've been working on some ideas related to community engagement with data, building data literacy in parent groups, and empowering underrepresented voices to tell their stories. And the more I read and think and develop these ideas, the more I recognize that there are some goals and outcomes that are bigger than I'd ever imagined. Serendipity has been an incredible guide and inspiration to this point, but I can't make the next leap (or two) with her alone. I'm going to have to have some real help.

Stage one: Build capacity in self
Not to be intentionally selfish, but this part of the process really is all about me. Perhaps you have projects where you are in the same mode. This has been a long-gestating stage. I went to my first Tapestry and Eyeo conferences more than two years ago. I've been building and sharing data stories in our district office for nearly that long. On the way, I've had to pick up new tools and skills and increase my personal network to call on experts and mentors. I don't believe that this stage will ever end—I will always be a learner. But I also think it's important to call it out separately as a base for everything else I want to support.

Stage two: Build capacity in organization
This past year, I've worked on not just sharing what I've learned at presentations and blog posts, but also leading workshops and building GitHub sites with resources. I've now seen others build their own data stories to share and grounded school leaders in our district in basic data literacy.

Stage three: Build partnerships outside of the organization
I am working on finding spaces outside of our district to host our data stories. Currently, Ready or Not is at our regional educational office and our story on graduation is at the state department of education. And last week, in a frisson of why-the-hell-not, I cold-called the data analytics business downtown and asked if they would host a window display during our city's fall Arts Walk. You see, I've recently been building "short stories"—smaller versions of the big displays—to take on the road. And while I won't claim that they are art, they are beautiful and good conversation starters. Why shouldn't I share them at a community event?

Another piece of stage three is a pilot project for next year where we will use some of the data therapy activities and other resources to increase data literacy in a parent or community group. But most importantly, this is not a project solely about pushing out some learning that we think is critical. It is about an opportunity to listen to the questions others have about our schools, as well as help them tell their own stories about what matters most to them about education. I am super-excited about this, even if I have no clue right now how to make this all happen.

Stage four: Empower the community
On one hand, this is really just an extension of stage three. If we do a pilot this year, then we will scale up afterward. But this is also where things get so big that it can't be "my" project anymore. This is a good thing. It means that I've been able to build enough capacity and partnerships that I can take a supporting role. What will all this look like? It might be a lot like the work showcased over at Making Sense. They have a whole toolkit ready and waiting. I also 💕 love 💕 this article on Data in Place: Thinking through Relations between Data and Community. I don't know what the outputs of this project will look like for us because we haven't implemented all of stage three yet. We will have to wait and see what our stakeholders think is the most critical issue to address.

So, there you have it. My plans for world data domination. Okay, maybe not as grand as all that, but I am hoping for a ripple that one day can become a wave. And this is where you come in, too, because everyone is welcome to join in. Are there activities you want to try, too, so we can learn from each other? Do you have connections or resources to share? What feedback or ideas do you have for us?

Friday, April 20, 2018

Seven: Care to Comment?

What do we say about our students? Do our values align with the words we use? Do they reflect what parents think is important about what happens in the classroom?

In this data story, we take a closer look at 3,694 comments written about 2,862 K - 5 students on their winter report cards.

The Data
Similar to last time, there wasn't anything especially fancy in terms of getting the data. We have reports in our student information system that will gather the information and spit it out into a spreadsheet. After that, I added student demographics and program information from another student file using trusty old INDEX/MATCH.

The big challenge part was getting the data clean...or, at least, cleanish. You see, I didn't want student names. Why not? In part because I wanted to make some of the data available to others. This means I needed to strip out identifying information from the text. Also, the names interfered with some of the frequency counting and comparisons I wanted to make. (Aside: Do you realize how many kids are go by the name "Maddie"? I didn't.)

I did a first pass using the SUBSTITUTE function in Excel. I had Excel replace any occurrences of a student's first name with "" to blank it out. However, this only worked when a teacher used the actual name of the student. Many kids go by nicknames, shortened versions of their names, first and middle names, etc. I'm sure there must be better ways than looking through things row by row, but that's what I ended up doing.

The Analysis
After the spreadsheets were all cleaned up and ready for church, I looked at some different options for doing the text analysis. I don't have any real experience with this, and while I looked as some fancy options like Overview, KH Coder, and Emosaic, I just didn't have the time to devote to digging into them right now. Instead, I used the WordCounter and SameDiff options over at

The WordCounter provided the basis for the word cloud you see in the picture at the top of this page. I used SameDiff to compare lists of comments for male and female students, for example.

There are also comparisons for students who receive special services (vs. those who don't), students eligible for free/reduced lunch (vs. those who aren't), and students of colour (vs. white).

I also used a couple of pivot tables in Excel to summarize and sort through the data—for example, the total number of comments per grade level or per student population.

The Build
Compared to the last few data stories we've built out in the hallway, this one is less complicated. There's a lot of paper and stickers, with some foam to help provide dimension to the word cloud.

I knew I wanted the background to be yellow...something bright for spring, but neutral enough that the black lettering could pop. We put the word cloud in the center of the board. It has the 50 most commonly used words. On the outside, we have the four pairs of lists with words that are only found in comments for students in a particular group. The list for our students who receive special services is particularly depressing.

But wait, there's more...

This is our first data story which uses two boards. On the second board, we have information for our students in secondary grades (6 - 12). There are two middle schools and two high schools. Teachers have a list of "canned" comments at each school that they can assign—two per class per grading period—as opposed to the freeform comments elementary teachers create. For these students, we did some simple counts of how many comments per student and then underneath those charts are lists of the most common and least common comments selected. On the right of the board, we have an area for people to leave comments for us.

This second board isn't as sexy as the one for elementary, but I'm still excited that we have represented something for every school and every K - 12 student (even if they received no comments).

Lessons Learned
This is one project where I would have loved to have rejected the null hypothesis: the idea that there isn't any difference between student groups. But even with this very basic analysis, I couldn't. Even though most of the text is pretty much the same across student groups at the elementary level, the bottom line is there are some differences in how we talk about boys and girls...and for students of colour...and students from low-income backgrounds...and those who receive special services.

We may never eliminate bias, but if we don't bring it to light, we can't start to address it. While it's great that our district is taking on several initiatives around inclusion and cultural competency, but these are useless if we only use them to pat ourselves on the back for starting them. If we can't change the system in meaningful ways for students, we are just as complicit as those who built the structures in the first place. This display is one way to raise some awareness of what we're up against.

To see more pictures of this project, or view frequency tables of the comments, please visit the page for this data story. As always, comments welcome!

Thursday, January 11, 2018

Six: Ready or Not

This (school) year, I have built a story about our high school seniors...and one for our sixth graders...and now I'm moving down to kindergarten. For our sixth data story, we are looking at early learning data. What does it mean to be kindergarten ready?

As usual, I didn't set out to tell this particular tale. I was totally going down a different path, thinking about student absences and creating some sort of strip plot...and as I doodled over dinner on the longest night of the year, The Muse came calling. And in about 10 minutes, I had the whole thing in mind about how to present our early learning data.

Our district has been participating in the state-mandated WaKIDS assessment for three years. Teachers collect observational data about each student's development in six categories: social-emotional, physical, cognitive, language, literacy, and math. There is a 9-level scale for each item, with birth to age 1 being the lowest and third grade being the highest. Only eight of these are shown below, as no child in our district was rated the lowest level in any category.

The Data
This story was one of the easiest in terms of managing the data files. The state provides us with a file of everything submitted by teachers, and then I merged in a few other demographic and program pieces. This time around, there were no statistical shenanigans, just total counts for each category and level.

The Build
Do you remember these? Usually built with pony beads, they have made various appearances throughout the years to signify friendship, solidarity, remembrance, or another purpose. Perhaps you wore them on your shoelaces or the lapel of a jacket.

If you haven't seen these sorts of things, they are constructed from safety pins and beads. I remembered them when I was still pondering the strip plot idea and veered off into how I might be able to string or hang beads from a line. Once I thought of the safety pins, I made an immediate connection to early learning (even if we don't use safety pins for diapers anymore).

After I had the concept, I knew I could build a safety pin with beads for each of our 486 kindergartners. Some back of the envelope calculations showed that I could fit 6 beads (at .5 - .6 mm each) on a 2" safety pin. This would allow me to show all six data points of the assessment, using beads with colours matching the developmental levels indicated by the teacher.

But what else could I encode, I wondered?

In divining the entrails of the data, I noticed that there were a few student attributes that might be worthy of further attention. First was gender. It is not uncommon to hear parents talking about "red shirting" young boys to give them an additional year to mature...but do the data bear this out? I ordered two types of safety pins to help us look at this: gold for girls and silver for boys. The second piece was a student's birthdate. We have a cutoff of September 1. If a student is not 5 years old by then, they can't enroll. But does that really matter---are older students more "ready"? I decided to encode this using different colours of map pins to attach the safety pins to the display. I picked red (because it was not one of the 8 colours of beads) for students who had a birthdate less than six months prior to the first day of school and white pins for older students. Finally, what about low income status? I didn't want to mark this by individual student, due to privacy issues; but, as I organized the pins by school, I decided to order the schools by their overall percentage of students who have low income status. That would give a general comparison. I did look at and consider race; however, I did not represent it with this display because (a) it was actually not as influential a factor as the others for this particular data set and (b) I couldn't represent it as accurately as it deserves. By this, I mean that with student privacy laws, by the time I made a pin showing race and gender, it could become very easy to associate the data with a particular child...especially as most of our schools might only have only one kindergarten student of a particular race. (Yes, we are very white.)

So here, is the final display:

The pins are organized in the space for each school by those kindergartners who were reported as most ready (all purple---or better---in the six categories) to least ready. As you can see in this broad shot, the school with the greatest percentage of low income students (PGS) has a lot lower proportion of all purple pins as compared to BLE, our school with the lowest percentage of low income students.

Here you can see the red vs. white map pins. Do you notice how many white are at the top and how many red are toward the bottom? This seems to tell us that age does matter a bit. Older kids are more ready. And I like seeing this, because while we might be able to talk about potential bias when it comes to gender, teachers don't have birthdays memorized or have an obvious way to connect them while working with students.

It's harder to see in the picture at the left (but you can click to embiggen), but gender also seems to play a role in how students are viewed in terms of readiness. Remember, gold pins represent girls...and by the time we get down to the bottom two rows, there is a lot of silver showing. I do wonder whether bias factors in here. I also noticed when I put the pins together that many of the girls were not rated as highly in math as they were in other areas. Hmmm.

Finally, you might notice the labels beneath each board. These are actually little booklets for each school with charts that show aggregate data. Viewers can look at the distributions for each category or for the demographics of the school. If you would like to see these charts, additional photos, or explore the web-based data workbook, please visit our district web site for this display.

Lessons Learned
One of my colleagues has said that this is his favourite story that I've built. I am very happy with it---we encoded a lot of information into a small space and were able to include every child. The pins jingle and move. The paper sparkles and feels sandy. Light refracts through the beads to make them glitter in the light. I think folding in elements of touch and sound is a critical piece of this work. I know that those aspects don't represent anything in particular about the data, but they invite people to ponder...and that's what I'm after: Engagement.

I also think it's interesting to compare schools and see how they used the scale for this assessment. One school (LRE) only used three levels---all of their pins only have purple, blue, or green beads. Another school (PGS) used eight levels and really differentiated. One school (MTS) is very large (106 kinders), but only 2 were rated as being kindergarten ready in all six areas, while all the other schools had a much larger proportion.

As we get ready to work with our community about registering kindergartners for next year, it will be interesting to think about how this display impacts our conversations. I already had one co-worker spend some time looking at it as she thinks about whether or not to enroll her son with a July birthday in school next year.

I am more than halfway through this project of building large-scale, analog, interactive data displays. My goal is to build ten...and I have four more to dream up and construct. The Muse will be back. I don't know when or what she'll bring, but I will be ready.